This study presents a new approach to evaluate potential sites for proposed hotel properties by designing an automated web GIS application: Hotel Location Selection and Analyzing Toolset (HoLSAT). The application uses a set of machine learning algorithms to predict various business success indicators associated with location sites. Using an example of hotel location assessment in Beijing, HoLSAT calculates and visualizes various desirable sites contingent on the specified characteristics of the proposed hotel. The approach shows considerable potential usefulness in the field of hotel location evaluation.
Keywords
Web GIS; Hotel location; Spatial decision making; Machine learning
Yang, Y. , Tang, J., Luo, H., and Law, R. (2015). Hotel location evaluation: A combination of machine learning tools and web GIS. International Journal of Hospitality Management, 47, 14-24.
Additional Reads
2026
Spatial heterogeneity of perceived visual quality along an urban sightseeing route: A route-contextualized point-level analysis
JOURNAL OF HOSPITALITY AND TOURISM MANAGEMENT
2026
When nature nurtures: Unlocking the healing power of soft adventure tourism
JOURNAL OF OUTDOOR RECREATION AND TOURISM
2026
Elevating excellence: Examining the effects of spatial competition on hotel quality